QAD AI is building the Persona Agent platform — the product that lets manufacturers deploy AI agents across procurement, sourcing, order management and planning. As we scale deployments through our Forward Deployed Engineering motion, the platform has to mature just as fast as the field learns. That is this role.
The Senior Applied AI Product Manager owns the Persona Agent platform roadmap end-to-end. You decide what the platform does out-of-the-box, what becomes reusable, and what stays a one-off — turning the signal coming back from real customer deployments into a coherent, defensible product. You report directly to the Head of AI and are the product counterpart to the field.
What You'll Own
1. The Persona Agent platform roadmap
You own the roadmap for the platform and its agent capabilities — the vision, the priorities, and the trade-offs. You decide what gets built, in what order, and why, and you hold the line on it.
Vision & strategy: Set and maintain the platform roadmap against a clear thesis of where agentic manufacturing software is going.
Prioritisation: Own the backlog, prioritisation and sequencing across competing customer and internal demands.
Platform vs. custom: Decide what belongs in the platform vs. what stays a customer-specific build — the single most important call you make repeatedly.
Agent scope: Define what a Persona Agent should do out-of-the-box for each process (P2P, O2C, S2C, P2M) and where the boundaries sit.
2. The field-to-product loop
The FDE team and AI Solutions Architects are deploying agents inside real customers every week, and each engagement surfaces patterns, gaps and hard-won solutions. You are the person who catches that signal and decides what becomes product. This loop is the engine of the platform — without it, the roadmap is guesswork; with it, every deployment makes the product better.
Capture: Run a structured intake of field signal — product gaps, recurring exception logic, integration patterns, autonomy models — from the FDE team and Architects.
Triage: Decide which field solutions are one-offs and which are patterns worth productising into reusable platform capabilities.
Productise: Turn recurring field builds (e.g. EDI error handling, chat-driven PO creation, per-category autonomy dials) into first-class product features.
Communicate: Close the loop back to the field so Architects and FDEs know what's coming and can design against it.
3. Delivery with engineering
You work hand-in-hand with the AI engineering and Applied AI teams to ship the roadmap — writing crisp specs, making scope calls, and keeping delivery honest against outcomes rather than output.
Specs: Write clear product specs and acceptance criteria that engineers can build against without ambiguity.
Metrics: Define how each capability's success is measured — adoption, agent performance, deployment-time saved — and track it.
Trade-offs: Make the hard scope trade-offs in the moment, and own the consequences.
4. Evaluation & quality of agent behaviour
Agent products live or die on whether the agent behaves. You own the product view of agent quality — defining what “good” looks like, and making sure evaluation is built into the platform, not bolted on.
Evals: Define the evaluation criteria for agent behaviour per process and per capability.
Instrumentation: Ensure attribution and telemetry are product requirements, so every deployment can prove impact.
Trust: Set the guardrails and autonomy defaults that keep agents safe and trustworthy in production.
How You Work With the Rest of the Org
You sit in the AI organisation reporting to the Head of AI, at the centre of the product, engineering and field triangle.
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AI Solutions Architects - Primary source of field requirements and validation; you turn their designs into repeatable product.
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FDE team (Services) - Your richest signal on what recurs across builds; you productise their accelerators.
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Applied AI / Engineering - Your build partners; you spec, prioritise and ship the roadmap with them.
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Head of AI - Your manager and the roadmap's executive owner; you bring the plan, the trade-offs and the field evidence.
